Merge branch 'main' of https://github.com/mouseland/mouseland.github.io

Author: carsen-stringer

code_and_data.qmd

@@ -1,5 +1,5 @@
 ---
-title: Code & data
+title: Code & datasets
 title-block-banner: true
 ---
 
@@ -16,25 +16,64 @@ We develop and maintain several analysis frameworks for neuroscience and biology
 <br>
 
 * [Suite2p](https://github.com/mouseland/suite2p) is a fast, accurate and complete pipeline written in Python that registers raw movies, detects active cells, extracts their calcium traces and infers their spike times. Suite2p runs on standard workstations, operates faster than real time, and recovers ~2 times more cells than the previous state-of-the-art methods. Its low computational load allows routine detection of ~25,000 cells simultaneously from recordings taken with standard two-photon resonant-scanning microscopes. In addition to its ability to detect cell somas, the detection algorithm can detect axonal segments, boutons, dendrites, and spines. Suite2p has an extensive GUI which allows the user to explore their data. Software developers have integrated Suite2p into their packages, such as those for multi-day cell alignment and photostimulation experiments.</p>
-<center><img src="http://www.suite2p.org/static/images/multiselect.gif" width="85%"></img></center>
+<center><img src="https://github.com/MouseLand/MouseLand.github.io/releases/download/v0.1/multiselect.gif" width="85%"></img></center>
 <br>
 
 * [Facemap](https://github.com/mouseland/facemap) is a tool for extracting behavioral features from mouse face videos and using them to predict neural activity. Facemap can be used to extract a 500-dimensional summary of the motor actions visible on the mouse’s face by applying singular value decomposition (SVD) to the facial motion. It can also be used to track keypoints on the mouse face, using a state-of-the-art deep neural network. Facemap also includes a 1D convolutional neural network to predict neural activity from keypoints or SVDs, which is two times more accurate than previous approaches. Facemap's GUI enables movie playback with behavioral feature tracking and neural activity.
 <center><img src="https://github.com/MouseLand/facemap/raw/master/figs/face_fast.gif" width="75%"></img></center>
 <br>
 
 * [Rastermap](https://github.com/mouseland/rastermap) is a tool for visualizing large-scale neural activity by applying a one-dimensional manifold embedding. To preserve both local and global structure, Rastermap combines manifold discovery and clustering. To capture temporal relationships among clusters, we compute not just the instantaneous correlations between cluster activities but also the cross-correlations of the clusters. Next we sort these clusters to optimize local and global distance preservation. Then the sorting is upsampled so that neurons can be assigned to their most correlated place in the one-dimensional embedding. This enables Rastermap to find sequences in visual cortical neural activity evoked by virtual reality corridors, which t-SNE and UMAP cannot do, and also Rastermap outperforms these algorithms on structure preservation benchmarks. Rastermap can be run in a jupyter-notebook, on the command line, in the provided GUI, or inside Suite2p to explore the spatial relationships among neurons identified to have similar activity patterns.
-<center><img src="https://www.suite2p.org/static/images/spont.gif" width="85%"></img></center>
+<center><img src="https://github.com/MouseLand/MouseLand.github.io/releases/download/v0.1/spont.gif" width="85%"></img></center>
 
 ## Datasets
 
 We share our large-scale recordings of mouse cortex on figshare:
 
-* [Recordings of 30k-70k neurons from visual and sensorimotor areas during spontaneous activity](https://janelia.figshare.com/articles/dataset/Facemap_a_framework_for_modeling_neural_activity_based_on_orofacial_tracking/23712957)
-* [Recordings of 20,000 neurons from V1 in response to oriented stimuli](https://figshare.com/articles/dataset/Recordings_of_20_000_neurons_from_V1_in_response_to_oriented_stimuli/8279387)
-* [Recordings of ten thousand neurons in visual cortex during spontaneous behaviors](https://figshare.com/articles/dataset/Recordings_of_ten_thousand_neurons_in_visual_cortex_during_spontaneous_behaviors/6163622)
-* [Recordings of 10,000 neurons in visual cortex in response to 2,800 natural images](https://figshare.com/articles/dataset/Recordings_of_ten_thousand_neurons_in_visual_cortex_in_response_to_2_800_natural_images/6845348)
-* [Eight-probe Neuropixels recordings during spontaneous behaviors](https://figshare.com/articles/dataset/Eight-probe_Neuropixels_recordings_during_spontaneous_behaviors/7739750) (recordings by Nick Steinmetz)
+-   [Visual response dataset (Du et al
+    2025)](https://janelia.figshare.com/articles/dataset/Towards_a_simplified_model_of_primary_visual_cortex/28797638):
+    recordings of 29,000 neurons in mouse primary visual cortex in
+    response to up to 65,000 natural images; [analysis
+    code](https://github.com/mouseland/minimodel)
+
+-   [Visual learning dataset (Zhong et al
+    2025)](https://doi.org/10.25378/janelia.28811129.v1): recordings of
+    50,000+ neurons simultaneously in mouse visual cortex as mice
+    undergo unsupervised and task learning in virtual reality; [analysis
+    code](https://github.com/mouseland/zhong-et-al-2025)
+
+-   [Facemap dataset (Syeda et al
+    2024)](https://janelia.figshare.com/articles/dataset/Facemap_a_framework_for_modeling_neural_activity_based_on_orofacial_tracking/23712957):
+    spontaneous neural activity from 50,000+ neurons in mouse visual
+    cortex and sensorimotor cortex, simultaneous face camera recordings,
+    and keypoint tracking training set
+
+-   [Neural responses to oriented stimuli (Stringer et al
+    2021)](https://figshare.com/articles/Recordings_of_20_000_neurons_from_V1_in_response_to_oriented_stimuli/8279387
+    ): Responses of 20,000+ neurons in mouse primary visual cortex and
+    higher order visual cortex; [analysis
+    code](https://github.com/mouseland/stringer-et-al-2019)
+
+-   [Spontaneous neural activity in V1 (Stringer, Pachitariu et al
+    2019)](http://dx.doi.org/10.25378/janelia.6163622.v6): Recordings of
+    10,000 neurons in visual cortex during spontaneous behaviors;
+    [analysis
+    code](https://github.com/MouseLand/stringer-pachitariu-et-al-2018a)
+
+-   [Eight-probe Neuropixels recordings during spontaneous
+    behaviors](https://figshare.com/articles/Eight-probe_Neuropixels_recordings_during_spontaneous_behaviors/7739750)
+    by Nicholas Steinmetz, from Stringer, Pachitariu et al 2019
+
+-   [Neural responses to natural images (Stringer, Pachitariu et al
+    2019)](http://dx.doi.org/10.25378/janelia.6845348.v4): Recordings of
+    10,000 neurons in primary visual cortex in response to 2,800 natural
+    images; [analysis
+    code](https://github.com/MouseLand/stringer-pachitariu-et-al-2018b)
+
+-   [V1 responses to drifting gratings (Pachitariu et al
+    2018)](https://figshare.com/articles/Recordings_of_10k_neurons_in_V1_during_drifting_gratings/6214019):
+    Responses of 10,000 neurons in mouse V1 during drifting gratings
+
 
 We also shared the training data for the Cellpose algorithm: [70,000 segmented cells + other objects](https://www.cellpose.org/dataset/).
 

index.qmd

@@ -6,20 +6,22 @@ resources:
 
 Our lab is at [HHMI Janelia Research Campus](https://www.janelia.org/) (near DC), a fully-funded non-profit research institution. Janelia just received a $500 million investment for AI research 🤖, more info [here](https://ai.hhmi.org/). 
 
-We are recruiting [PhD students](positions.qmd)!
+We are recruiting [postdocs](positions.qmd)!
 
 ## Research
 
 Our lab combines machine learning / AI techniques and large-scale imaging to investigate plasticity rules and sensory representations in cortical circuits. Example recording of 50,000+ neurons simultaneously at 3Hz, using two-photon calcium imaging:
 
 <video width="100%" autoplay loop muted playsinline controls alt="50,000 neurons recorded with two-photon calcium imaging from mouse visual cortex">
-  <source src="https://www.suite2p.org/static/images/Movie1.mp4" type="video/mp4">
+  <source src="https://github.com/MouseLand/MouseLand.github.io/releases/download/v0.1/Movie1.mp4" type="video/mp4">
 </video>
 
 Learn more about our research [here](research/index.qmd) and see all publications [here](research/publications.qmd). We share all the data generated by our studies, linked [here](code_and_data.qmd). We also have developed several data processing packages for the bio/neuro community: [cellpose](research/posts/cellpose.qmd), [kilosort](research/posts/kilosort.qmd), [suite2p](research/posts/suite2p.qmd), [facemap](research/posts/rastermap.qmd), and [rastermap](research/posts/rastermap.qmd).
 
 ## News
 
+* Fengtong Du's [paper](https://www.nature.com/articles/s41467-025-61171-9) on minimodels of visual cortical neurons in mice and monkeys now published! [News coverage](https://www.janelia.org/news/new-computational-model-could-help-shed-light-on-how-we-see)
+* Lin Zhong's [paper](https://www.nature.com/articles/s41586-025-09180-y) on unsupervised learning now published! [News coverage](https://www.janelia.org/news/zoning-out-could-be-beneficial%E2%80%94and-may-actually-help-us-learn-faster)
 * [Cellpose3](https://www.nature.com/articles/s41592-025-02595-5) now published! [News coverage](https://www.janelia.org/news/newest-version-of-cellpose-can-spot-cell-boundaries-even-in-cloudy-conditions)
 * [Analysis methods for large-scale neuronal recordings](https://www.science.org/stoken/author-tokens/ST-2239/full) review published!
 * Cellpose development highlighted in a Nature [technology feature](https://www.nature.com/articles/d41586-024-03344-y)!
@@ -33,7 +35,6 @@ Learn more about our research [here](research/index.qmd) and see all publication
 
 * About [HHMI Janelia Research Campus](https://www.janelia.org/about-us)
 * HHMI's [values](https://www.hhmi.org/about/values)
-* HHMI’s [commitment to Diversity, Equity, and Inclusion](https://diversity.hhmi.org/)
 * [Being a postdoc at Janelia](https://youtube.com/playlist?list=PLTHgpZlI_u0hSo_NO0wpzpMnt6BnOOaWl&feature=shared)
 
 ## Talks
@@ -55,6 +56,14 @@ Learn more about our research [here](research/index.qmd) and see all publication
 
 ## Media Coverage
 
+- [New computational model could help shed light on how we see](https://www.janelia.org/news/new-computational-model-could-help-shed-light-on-how-we-see), Howard Hughes Medical Institute
+
+- [Doing This Might Actually Make You Smarter](https://www.vice.com/en/article/doing-this-might-actually-make-you-smarter/), Vice
+
+- ["Zoning Out" Actually Helps You Learn? Data From Up To 90,000 Brain Cells Says So](https://www.iflscience.com/zoning-out-actually-helps-you-learn-data-from-up-to-90000-brain-cells-says-so-79986), IFL Science
+
+- [Zoning out could be beneficial—and may actually help us learn faster](https://www.janelia.org/news/zoning-out-could-be-beneficial%E2%80%94and-may-actually-help-us-learn-faster), Howard Hughes Medical Institute
+
 - [Newest version of Cellpose can spot cell boundaries even in cloudy conditions](https://www.janelia.org/news/newest-version-of-cellpose-can-spot-cell-boundaries-even-in-cloudy-conditions), Howard Hughes Medical Institute
 
 - [Novel visualization method helps make sense of large neuronal activity datasets](https://medicalxpress.com/news/2024-10-visualization-method-large-neuronal-datasets.html), Medical Xpress

positions.qmd

@@ -3,11 +3,10 @@ title: "Positions"
 title-block-banner: true
 ---
 
-## PhD students
+## Postdocs
 
-We are seeking [PhD students](https://www.janelia.org/you-janelia/students-and-postdocs/joint-graduate-programs) (through JHU) to investigate how large populations of neurons perform complex computations. We collect and analyze recordings of 50,000+ neurons, developing machine learning tools to extract computational principles from these large-scale datasets. Feel free to reach out to Carsen Stringer (<[email protected]>) with your CV if you are interested and have any questions. Applications should be submitted by **Dec 1 2024** to the [neuroscience department](https://neuroscience.jhu.edu/graduate) or the [XDBio department](https://xdbio.jhmi.edu/) at JHU. Fee waivers are available through the departments.  Please share a link to your github profile on your CV when applying.
+We are seeking [postdocs](hhttps://www.janelia.org/you-janelia/students-postdocs/postdoctoral-scientists) to investigate how large populations of neurons perform complex computations. We collect and analyze recordings of 50,000+ neurons, developing machine learning tools to extract computational principles from these large-scale datasets. Please reach out to Carsen Stringer (<[email protected]>) with your CV if you are interested. We are looking for candidates with experience performing imaging experiments in animals and ideally some experience analyzing large-scale neural datasets. Please share a link to your github profile on your CV when applying, especially if you are coming from a computational background.
 
+All research is internally funded by the Howard Hughes Medical Institute with highly competitive benefits. A first-year postdoc is compensated at a rate of $74,200.00 annually. For information about Janelia, please visit [www.janelia.org/about-us](http://www.janelia.org/about-us). For more information about our neuroscience department, please visit [www.janelia.org/our-research/mechanistic-cognitive-neuroscience](https://www.janelia.org/our-research/mechanistic-cognitive-neuroscience). For more information about being at Janelia, please check out these [videos](https://youtube.com/playlist?list=PLTHgpZlI_u0hSo_NO0wpzpMnt6BnOOaWl&feature=shared). Janelia provides incredible support for scientific research (surgical support, animal behavior training, and optical engineering), enabling researchers to focus on their specific scientific questions.
 
-All research is internally funded by the Howard Hughes Medical Institute with highly competitive benefits. For information about Janelia, please visit [www.janelia.org/about-us](http://www.janelia.org/about-us). For more information about our neuroscience department, please visit [www.janelia.org/our-research/mechanistic-cognitive-neuroscience](https://www.janelia.org/our-research/mechanistic-cognitive-neuroscience). For more information about being at Janelia, please check out these [videos](https://youtube.com/playlist?list=PLTHgpZlI_u0hSo_NO0wpzpMnt6BnOOaWl&feature=shared). Janelia provides incredible support for scientific research (surgical support, animal behavior training, and optical engineering), enabling researchers to focus on their specific scientific questions.
-
-Diversity, equity and inclusion are important values at Janelia, and applicants should be dedicated to ensuring kindness and inclusion in their interactions with the scientific community and with other employees at Janelia. See more details about HHMI's commitment to diversity here: <https://diversity.hhmi.org/>.
+Diversity, equity and inclusion are important values at Janelia, and applicants should be dedicated to ensuring kindness and inclusion in their interactions with the scientific community and with other employees at Janelia.

research/posts/highdim.qmd

@@ -31,7 +31,7 @@ A neuronal population encodes information most efficiently when its stimulus res
 <hr>
 
 1. A picture is worth a thousand words, and your brain needs billions of neurons to process it. Why do we need so many neurons? To find out, we recorded thousands of them in mouse visual cortex. </p>
-<p><video src='https://www.suite2p.org/static/images/stimresp.mp4' width="90%" loop="true" autoplay="autoplay" controls muted></video></p>
+<p><video src='https://github.com/MouseLand/MouseLand.github.io/releases/download/v0.1/stimresp.mp4' width="90%" loop="true" autoplay="autoplay" controls muted></video></p>
 
 2. One reason to have so many neurons may be that they each have different jobs: </p>
 Neuron A recognizes the pointedness of a fox’s ears,<br>
@@ -85,10 +85,10 @@ etc</p>
 19. However, this was not just any power-law, it had a special exponent of approx 1. We did some math and showed that a power-law with this exponent must be borderline fractal.</p>
 
 20. A fractal is a mathematical object that has structure at many different spatial scales, like the Mandelbrot set below:</p>
-<p><video src='https://www.suite2p.org/static/images/fractal.mp4' width="90%"  loop="true" autoplay="autoplay" controls muted></video></p>
+<p><video src='https://github.com/MouseLand/MouseLand.github.io/releases/download/v0.1/fractal.mp4' width="90%"  loop="true" autoplay="autoplay" controls muted></video></p>
 
 21. This Inceptionism movie is also a kind of fractal:</p>
-<p><video src='https://www.suite2p.org/static/images/inception.mp4' width="90%"  loop="true" autoplay="autoplay" controls muted></video></p>
+<p><video src='https://github.com/MouseLand/MouseLand.github.io/releases/download/v0.1/inception.mp4' width="90%"  loop="true" autoplay="autoplay" controls muted></video></p>
 
 22. The neural activity was so close to being a fractal, and just barely avoided it because it’s exponent was 1.04, not 1 or smaller.</p>
 

research/posts/highprecision.qmd

@@ -38,7 +38,7 @@ Thread:
 1. Single neurons in the brain can’t be depended on for reliable information.
 Here are some neurons from our recent study, recorded twice in response to the same visual stimuli.
 Different neurons are active at different times!
-<p><video src='https://www.suite2p.org/static/images/two_repeats.mp4' width="90%" loop="true" autoplay="autoplay" controls muted></video></p>
+<p><video src='https://github.com/MouseLand/MouseLand.github.io/releases/download/v0.1/two_repeats.mp4' width="90%" loop="true" autoplay="autoplay" controls muted></video></p>
 
 2. Ask a neuron what angle the corner of your screen makes and it will say 75 degrees right now, 100 degrees in 5 minutes, and some other random number close to 90 every time you ask.</p>
 <img src='images/hp1.jpg' width="70%"></p>

research/posts/images/kilosort_logo_small.png

@@ -9,7 +9,7 @@ date: Mar 2024
 date-format: MMM YYYY
 author: Marius Pachitariu, Shaswat Sridhar, Jacob Pennington, Carsen Stringer
 toc: false
-image: http://www.kilosort.org/static/downloads/kilosort_logo_small.png
+image: images/kilosort_logo_small.png
 image-alt: spikes colored by amplitude along probe
 ---